scholarly journals Graph analysis of functional brain networks for cognitive control of action in traumatic brain injury

Brain ◽  
2012 ◽  
Vol 135 (4) ◽  
pp. 1293-1307 ◽  
Author(s):  
Karen Caeyenberghs ◽  
Alexander Leemans ◽  
Marcus H. Heitger ◽  
Inge Leunissen ◽  
Thijs Dhollander ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Cognitive Control ◽  
Brain Networks ◽  
Graph Analysis ◽  
Functional Brain ◽  
Functional Brain Networks

scholarly journals Graph Analysis of Functional Brain Networks in Patients with Mild Traumatic Brain Injury

PLoS ONE ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. e0171031 ◽  
Author(s):  
Harm J. van der Horn ◽  
Edith J. Liemburg ◽  
Myrthe E. Scheenen ◽  
Myrthe E. de Koning ◽  
Jacoba M. Spikman ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Brain Networks ◽  
Graph Analysis ◽  
Functional Brain ◽  
Functional Brain Networks

scholarly journals Changes in intrinsic functional brain networks following blast-induced mild traumatic brain injury

Brain Injury ◽  
2013 ◽  
Vol 27 (11) ◽  
pp. 1304-1310 ◽  
Author(s):  
Andrei A. Vakhtin ◽  
Vince D. Calhoun ◽  
Rex E. Jung ◽  
Jillian L. Prestopnik ◽  
Paul A. Taylor ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Brain Networks ◽  
Functional Brain ◽  
Functional Brain Networks

scholarly journals Subgraphs of functional brain networks identify dynamical constraints of cognitive control

2018 ◽  
Vol 14 (7) ◽  
pp. e1006234 ◽  
Author(s):  
Ankit N. Khambhati ◽  
John D. Medaglia ◽  
Elisabeth A. Karuza ◽  
Sharon L. Thompson-Schill ◽  
Danielle S. Bassett
Keyword(s):  
Cognitive Control ◽  
Brain Networks ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
Dynamical Constraints

scholarly journals Disruption to functional networks in neonates with perinatal brain injury predicts motor skills at 8 months

2017 ◽  
Author(s):  
Annika C. Linke ◽  
Conor Wild ◽  
Leire Zubiaurre-Elorza ◽  
Charlotte Herzmann ◽  
Hester Duffy ◽  
...  
Keyword(s):  
Brain Injury ◽  
Functional Connectivity ◽  
Motor Skills ◽  
Brain Networks ◽  
Motor Impairment ◽  
Structural Mri ◽  
Perinatal Brain Injury ◽  
Diverse Range ◽  
Functional Brain ◽  
Functional Brain Networks

AbstractObjectiveFunctional connectivity magnetic resonance imaging (fcMRI) of neonates with perinatal brain injury could improve prediction of motor impairment before symptoms manifest, and establish how early brain organization relates to subsequent development. Methods: This cohort study is the first to describe and quantitatively assess functional brain networks and their relation to later motor skills in neonates with a diverse range of perinatal brain injuries. Infants (n=65, included in final analyses: n=53) were recruited from the neonatal intensive care unit (NICU) and were stratified based on their age at birth (premature vs. term), and on whether neuropathology was diagnosed from structural MRI. Functional brain networks and a measure of disruption to functional connectivity were obtained from 14 minutes of fcMRI acquired during natural sleep at term-equivalent age.ResultsDisruption to connectivity of the somatomotor and frontoparietal executive networks predicted motor impairment at 4 and 8 months. This disruption in functional connectivity was not found to be driven by differences between clinical groups, or by any of the specific measures we captured to describe the clinical course.ConclusionfcMRI was predictive over and above other clinical measures available at discharge from the NICU, including structural MRI. Motor learning was affected by disruption to somatomotor networks, but also frontoparietal executive networks, which supports the functional importance of these networks in early development. Disruption to these two networks might be best addressed by distinct intervention strategies.

scholarly journals Awakening after a sleeping pill: Restoring functional brain networks after severe brain injury

Cortex ◽  
2020 ◽  
Vol 132 ◽  
pp. 135-146
Author(s):  
Hisse Arnts ◽  
Willemijn S. van Erp ◽  
Lennard I. Boon ◽  
Conrado A. Bosman ◽  
Marjolein M. Admiraal ◽  
...  
Keyword(s):  
Brain Injury ◽  
Brain Networks ◽  
Severe Brain Injury ◽  
Functional Brain ◽  
Functional Brain Networks

scholarly journals Functional brain networks associated with cognitive control, cocaine dependence, and treatment outcome.

2013 ◽  
Vol 27 (2) ◽  
pp. 477-488 ◽  
Author(s):  
Patrick D. Worhunsky ◽  
Michael C. Stevens ◽  
Kathleen M. Carroll ◽  
Bruce J. Rounsaville ◽  
Vince D. Calhoun ◽  
...  
Keyword(s):  
Treatment Outcome ◽  
Cognitive Control ◽  
Brain Networks ◽  
Cocaine Dependence ◽  
Functional Brain ◽  
Functional Brain Networks

scholarly journals Correction: Subgraphs of functional brain networks identify dynamical constraints of cognitive control

2018 ◽  
Vol 14 (8) ◽  
pp. e1006420 ◽  
Author(s):  
Ankit N. Khambhati ◽  
John D. Medaglia ◽  
Elisabeth A. Karuza ◽  
Sharon L. Thompson-Schill ◽  
Danielle S. Bassett
Keyword(s):  
Cognitive Control ◽  
Brain Networks ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
Dynamical Constraints

scholarly journals Graph analysis of functional brain networks: practical issues in translational neuroscience

2014 ◽  
Vol 369 (1653) ◽  
pp. 20130521 ◽  
Author(s):  
Fabrizio De Vico Fallani ◽  
Jonas Richiardi ◽  
Mario Chavez ◽  
Sophie Achard
Keyword(s):  
Brain Networks ◽  
Brain Network ◽  
Graph Analysis ◽  
Translational Neuroscience ◽  
Functional Brain ◽  
Functional Perspective ◽  
Brain Signals ◽  
Functional Brain Networks ◽  
The One ◽  
The Brain

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes.

scholarly journals Alterations of connectivity patterns in functional brain networks in patients with mild traumatic brain injury: A longitudinal resting-state functional magnetic resonance imaging study

2020 ◽  
Vol 33 (2) ◽  
pp. 186-197 ◽  
Author(s):  
Maria M D’Souza ◽  
Mukesh Kumar ◽  
Ajay Choudhary ◽  
Prabhjot Kaur ◽  
Pawan Kumar ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Traumatic Brain Injury ◽  
Magnetic Resonance ◽  
Functional Connectivity ◽  
Resting State ◽  
Brain Networks ◽  
Network Connectivity ◽  
Resonance Imaging ◽  
Functional Brain ◽  
Functional Brain Networks

Aim In the present study, we aimed to characterise changes in functional brain networks in individuals who had sustained uncomplicated mild traumatic brain injury (mTBI). We assessed the progression of these changes into the chronic phase. We also attempted to explore how these changes influenced the severity of post-concussion symptoms as well as the cognitive profile of the patients. Methods A total of 65 patients were prospectively recruited for an advanced magnetic resonance imaging (MRI) scan within 7 days of sustaining mTBI. Of these, 25 were reassessed at 6 months post injury. Differences in functional brain networks were analysed between cases and age- and sex-matched healthy controls using independent component analysis of resting-state functional MRI. Results Our study revealed reduced functional connectivity in multiple networks, including the anterior default mode network, central executive network, somato-motor and auditory network in patients who had sustained mTBI. A negative correlation between network connectivity and severity of post-concussive symptoms was observed. Follow-up studies performed 6 months after injury revealed an increase in network connectivity, along with an improvement in the severity of post-concussion symptoms. Neurocognitive tests performed at this time point revealed a positive correlation between the functional connectivity and the test scores, along with a persistence of negative correlation between network connectivity and post-concussive symptom severity. Conclusion Our results suggest that uncomplicated mTBI is associated with specific abnormalities in functional brain networks that evolve over time and may contribute to the severity of post-concussive symptoms and cognitive deficits.

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